Sales Performance Analysis of
High Impact Careers
This presentation explores the sales performance of High Impact Careers. It
covers data cleaning, analysis, and visualization, culminating in actionable
insights and recommendations.
by Oluwatosin Giwa
Data Preparation and Cleaning
Initial Data Examination
The dataset, an Excel file with 34,867 rows and 15 columns,
contained information on order ID, date, customer details,
salesperson, branch, product category, and sales metrics.
Data Cleaning in Excel
The initial step involved standardizing date formats, renaming
and ordering headers, and correcting data types to ensure
data consistency and clarity.
Creating Dimension Tables
Customer Table
This table contained customer name, type, age, and gender, with
unique IDs created to link it to the fact table.
Product Table
This table included product ID, category, and subcategory, also with
unique IDs for linking.
Data Analysis and Visualization in Power BI
Key Performance Indicators (KPIs)
Power BI enabled the calculation and visualization of KPIs such
as total customers, product costs, revenue, profits, quantity
sold, and average customer age.
Detailed Insights
Analysis focused on profit by age group, product category, and
subcategory, as well as annual and quarterly profit trends and
salesperson performance.
Interactive Filtering
1
Date
Users could filter data by specific dates, years, and
months to analyze trends over time.
2
Product Subcategory
Interactive filters allowed users to drill down into specific
product subcategories to understand their performance.
Recommendations
Focus on Profitable Age Groups
Marketing efforts should be tailored to the most profitable age groups.
Optimize Product Offerings
Increase inventory and promotional efforts for high-performing product categories and subcategories.
Seasonal Promotions
Leverage insights from quarterly trends to run targeted promotions during peak periods.
Salesperson Training
Implement training programs based on the practices of top-performing salespersons to boost overall sales performance.
Conclusion
1
Data-Driven Insights
The analysis provided a comprehensive understanding of sales dynamics, leading
to informed recommendations.
2
Actionable Recommendations
The insights can be used to drive business growth and improve sales
performance.
3
Value of Data Analysis
This project underscored the importance of data-driven
decision-making in today's business environment.
Next Steps
The next steps involve implementing the recommendations, monitoring
the impact on sales performance, and continuously refining the analysis
process. This will ensure that High Impact Careers continues to optimize its
sales strategies and achieve its business goals.